1. Introduction

In Kenya, public health amenities struggle to provide basic services owing to human resource challenges, inadequate commodities attributed to poor inventory management and supply chain management practices, poor financing of health systems, weak institutional arrangements, and under developed organizational ethics codes (Waithaka et al., 2020). Agreeing to a World Health Organization (WHO) report (2018), there has been a 25-year of global decline (44%) of MMR to around 216 deaths per 100,000 live births in 2015 from 385 in 1990. The 2019 Kenya Population and Housing Census Results pointed to slow progress in maternal, neonatal and child health outcomes with a maternal mortality ratio of 355/per 100,000 live births, an infant mortality rate of 35.5/per 1000 live births, and an under 5 mortality rate of 52/1000 live births(KNBS, 2019). The rate of decline is slow such that the attainment of sustainable development goals targets is unlikely (SDG target 3.1 for maternal mortality is 70/100,000 live births and for neonatal mortality (SDG target 3.2) is 12/1000 live births) (World Health Organization, 2015). Empirical studies have confirmed that antenatal care (ANC) visits, institutional delivery with skilled birth attendants (SBA), and postnatal care are vital in preventing maternal and newborn deaths (Gülmezoglu et al., 2016).

Inequality in the provision and access to health services for mothers and children is prevalent in Kenya. Geographic accessibility from home to health facilities is considered a major barrier to access to adequate maternal and child health services (Tanou et al., 2021). The negative association between distance or travel time to health facilities and use of health services has been shown to be a significant barrier to access to health services. This is because many life-saving interventions, such as caesarean sections and blood transfusions, are only available at the medical facility to which they are referred (Tounkara et al., 2022). This geographical barrier is represented by the second delay in the 3-delays model. (1) Delays in decision making, (2) delays in reaching medical facilities, and (3) delays in adequate care. (Mohammed et al., 2020). Besides, good infrastructure according to (Quattrochi et al., 2020; Sgaier et al., 2015), is essential not just for persons seeking healthcare services but also for easy distribution of medical products and faster referrals in case of emergencies. Inadequate resources have an impetus on facility outcomes such as quality and safety of care delivered. Community-based interventions can significantly reduce neonatal and maternal mortality (Lassi et al., 2010).

Similarly, tracer item availability is low, suggesting the need to expand coverage in primary health care settings to accelerate and achieve reductions in maternal and neonatal mortality and meet SDGs 3.1 and 3.2. In Kenya 50% of facilities offer delivery services with significant gaps in the availability of tracer items for Comprehensive Emergency Obstetric and Newborn Care (CEmONC) and Basic emergency obstetric and newborn care (BEmONC) services. This compromises the availability and quality of a lifesaving service to the mother and baby. The mean availability of tracer items required for a facility to be considered ready to offer CEmONC services is 70% with only 1% of facilities having all the tracer items. Similarly, mean availability of BEmONC is 68% nationally with the availability of all tracer items at 3% (MOH, 2019).

In 2013, Kenya abolished charges in all public maternity wards, promoting eligible birth attendance and aftercare for newborns and children. The introduction of various health payment schemes, such as the National Health Insurance Fund (NHIF), Output-Based Aid, Changamuka, Jamii Bora and Linda Mama. It has made it possible for women to have access to appropriate support during childbirth, minimizing long-standing inequalities between urban, rural and poor people. Linda Mama has been developed, improved accountability, and expanded benefits, but beneficiaries still do not have access to some benefits that were part of the revised benefits package e.g newborn care. Therefore, beneficiaries still had to pay out of pocket, and most county health facilities lost their financial autonomy as they were unable to receive reimbursement from NHIF for services rendered. In addition, disbursement of funds from NHIF may be delayed or unpredictable. (Orangi et al., 2021).

Furthermore, the inability to quantify and analyze the situation using reliable data plagues Kenya. The health system lacks the ability to measure or understand its own weaknesses and limitations, and policy makers have no science-based idea of what can or should actually be strengthened (Hotchkiss et al., 2010). To facilitate interpretation of national reports and to provide guidance on data use in decision making, (Kihuba et al., 2014) conducted an evaluation of core functions of data generation and reporting within hospitals in Kenya. The study findings indicated that only a few HMIS departments (3/22) had carried out a data quality audit in the 12 months before the survey. Completeness of manual patient registers varied, being 90%, 75.8% and 58% in the maternal-child health clinic, maternity, and pediatric wards, respectively. Vital events notification rates were low with 25.7%, 42.6%, and 71.3% of neonatal deaths, infant deaths, and live births recorded, respectively.

Routine hospital reports suggested slight over-reporting of live births and under-reporting of fresh stillbirths and neonatal deaths. The National Maternal and Perinatal Death Surveillance and Response guideline directs the conduct of Maternal and Perinatal Death Reviews (MPDRs) and near-miss reviews in the community and the health facilities in Kenya. A confidential investigation into the 2017 Maternal Death Report in Kenya found that the majority of audited maternal deaths were poorly recorded and documented. As a result, improving the quality of maternal health requires the use of information technology to facilitate communication and enable faster care and shorter turnaround times. (Delaney, 2018). However, weak ICT infrastructure is evident in low- and middle-income countries. Improving the quality of care for mothers and newborns demands for the health system be prepared in terms of the availability of all resources required (Das et al., 2021; Tunçalp et al., 2015).

These factors are part of the drivers to the slow progression in maternal and child mortality that has seen Kenya ranked among the ten most dangerous countries for a woman to give birth in the world (UNFPA, 2020). Counties in the North-Eastern part of Kenya have the poorest maternal indicators with Garissa recording the highest MMR of 641/per 100,000 live births, an IMR of 42.1, and U5MR of 64.6. Nairobi county is reported to have the highest number of absolute maternal mortalities given its population.

These two counties are part of the 15 high burden counties for maternal mortality in Kenya. There is a need to maintain investments in MCH care in Garissa and Nairobi counties. However, accelerating progress requires robust and sustainable MCH interventions that are readily adaptable and integrate fluidly into the local systems. Transferability of these MCH interventions relies on evidence-based and context-specific evaluations. One critical weakness across the Nairobi and Garissa counties is the current lack of capacity to effectively monitor patterns of service use through time so that the impacts of changes in policy or service delivery can be evaluated. Moreover, there is a dearth of data on the drivers to poor MCH outcomes in Nairobi and Garissa counties. As such, this situational analysis sought to explore the main vulnerabilities in the two counties, highlighting the ongoing challenges facing their systems and people and to inform and plan interventions that lower maternal, neonatal, and child morbidity and mortality rates.

2. Methods

Study Setting and participants

This cross-sectional study was conducted in Nairobi and Garissa counties in June 2022. The counties were first purposively selected then cluster sampling followed to select the sub-counties with poor MCH indicators and those in informal settlements in Nairobi. The study sites in Nairobi included Ruaraka and Embakasi North sub-Counties while the study sites in Garissa County included Fafi, Lagdera and Balambala. The MCH indicators for the two counties are summarized in Table 1 below. The target population included county health management teams, men, women, healthcare providers, traditional birth attendants (TBA), chiefs, health records information officers, and community health extension workers. The targeted number of health facilities in Nairobi were nine, while those in Garissa were four.

Table 1. MCH indicators 2021

Study Design

This study adopted a mixed method approach. Qualitative responses examined the experiences, voice and agency of the women, men, county health management teams, traditional birth attendants (TBA), chiefs, and community health extension workers. The quantitative data assessed population access to services, human resource availability, MCH service availability, infrastructure and equipment availability, commodity availability, availability of protocols, guidelines and training materials, and ICT technology. Insights gained from quantitative and qualitative approaches were triangulated to provide an in-depth understanding of the main vulnerabilities in the two counties and the challenges facing their systems.

Data collection tools included open and closed questionnaires, an observation checklist, structured key informant interview guides and focus group discussions. All questionnaires were self-administered. They were dropped and picked at an agreed time with the respondents. On average, observations took a full day, and FGDs took 30–60 minutes.

Data management and analysis

The data collection tools were programmed on the Open Data Kit (ODK) software. Quantitative data was uploaded from the phone/tablet by the research assistants (RAs) at the end of each day and downloaded by the supervisors for screening to check for completeness, identify any gaps/issues with feedback provided to the RAs during debriefing sessions for action to address gaps identified on subsequent days. Quantitative data were analyzed using SPSS version 25.

Descriptive statistics was the principal data analysis technique for quantitative data. For qualitative data, the transcribed texts were transferred to NVIVO 8 qualitative analysis software and analyzed. Following the coding of the transcripts, a full list of themes was categorized within a hierarchical framework of main and sub-themes. The thematic framework was then systematically applied to all the interview transcripts. Patterns and associations of the themes were identified and compared within and between the different groups of respondents to enhance the triangulation of data.

Ethical considerations

Our ethical approach followed Declaration of Helsinki and complied with all its guidelines. After stipulating the objectives, procedures, risks, benefits, confidentiality and voluntary both verbally and literally, the respondents who were willing to participate were asked for a signature on the informed consent form. For those unable to read and write, witnesses their families, relatives or neighbors were asked to sign the form on their behalf. Additionally, for those aged below 18 years, their guardians were asked to accompany, and then sign the informed ascent. Permission was sought from the relevant health facilities management and all stakeholders were also informed about the study.

3. Results

Study participant characteristics

This section gives an in-depth description of the findings of the situational analysis. A total of 391 respondents participated in the study. There was a 100% response rate. See Table 2 below for a breakdown of the total number of respondents from Nairobi and Garissa counties.

Table 2. Total Number of participants

Services Availability

The study findings revealed that maternal health services and other sexual and reproductive health care such as family planning, emergency contraception, treatment of sexually transmitted infections, and legal safe abortion services were available as core health services in both Nairobi and Garissa counties. All (100%) of the facilities in Garissa and Nairobi counties provide family planning services while only 22% of these facilities offer safe abortion services. Table 3 below gives a snapshot of the services offered by county and level of facility.

Table 3. Service Availability (%)

Maternal medicine availability

Table 4 illustrates maternal medicine availability for Nairobi and Garissa counties. Oxytocin was readily available in most facilities in both counties. Misoprostol for Postpartum Hemorrhage (PPH) prevention was unavailable for all facilities in Garissa County based on the responses. In Nairobi County, 33.3% of respondents from level 2 facilities and 60% from level 3 facilities agreed to having Misoprostol in their facilities in adequate quantities. Calcium gluconate is inadequate in level 2 and level 3 facilities in Garissa County. In contrast, 50% of respondents agreed that Calcium gluconate was adequate in their facilities. In Nairobi County, 33.3% of respondents from level 2 facilities and 40% from level three facilities agreed that Calcium gluconate was adequate in their facilities. See table 4 below for more details.

Table 4. Maternal Medicine Availability (%)

Basic Emergency Obstetric and Neonatal Care (BEMONC) Service Availability

As shown in Table 5 the study revealed that most level four facilities had the seven signal functions for emergency obstetric and neonatal care. Level 2 facilities were observed to have less adequacy basic emergency obstetric and neonatal care availability.

Table 5. Availability of Basic Emergency Obstetric and Neonatal Care Services availability

Findings from the FGDs with women revealed that they preferred visiting a trained medic at a health facility because of their expertise, and the ability to detect complications early and provide definitive care.

“I prefer to visit a trained medic at a health facility. It helps avoid risks that come during birth that might lead to the death of the infant. The baby can also get the immunization immediately after birth in a health facility as opposed to when helped by a TBA” -Respondent one

Infrastructure and Equipment Availability

The findings revealed a high availability of essential health infrastructure and equipment in level 4 facilities compared to level 2 and facilities. The surveyed facilities had inadequate access to functional incubators in the neonatal wing of the facilities, resuscitation devices, pharmacy, functional ambulances, a sufficiently equipped theater to handle cesareans operations, an incinerator, proper storage for blood, beds, and room for MCH services at level 2 and 3 facilities in Garissa County. All (100%) level 2 facilities in Nairobi County lacked a functional ambulance and a sufficiently equipped theater to handle cesareans operations. The level three facilities lacked proper storage for blood and the ability to perform a blood transfusion. See table 6 below for more details.

Table 6. Infrastructure and Equipment Availability (%)

Safe and Clean delivery conditions

Clean delivery practices anchored on the “six cleans” (clean hands, clean surface, clean blade, clean cord tie clean towel to wrap baby, and clean cloth for mother) prevent maternal and neonatal infections and should constitute safe and clean delivery practices. The condition of the “six cleans” for safe and clean delivery services by county and sub-County is presented in Table 7 below.

Table 7. Safe and Clean delivery conditions (%)

All respondents from Balambala and Fafi in Garissa County acknowledged that they lacked clean bedsheets, clean clothes/baby towels for wrapping the baby. The situation was however different for Nairobi County. Sterile blades were available in all (100%) facilities in Balambala, Fafi, Lagdera and Embakasi North sub-County. In contrast, only 40% of facilities in the Ruaraka sub-County had sterile blades. While none of the facilities in Balambala and Fafi had a room heater, 50% in Lagdera and Embakasi North sub-County had room heaters. In the Ruaraka sub-county, only 20% of the facilities had heaters.

While all (100%) facilities in Fafi and Lagdera had sterile codes ties available, none in Balambala had sterile codes ties. In Nairobi County, only 60% of facilities in Ruaraka sub-County had sterile codes ties compared to 50% in Embakasi North sub-County. All (100%) facilities in Balambala, Lagdera and Embakasi North sub-County had access to clean water, disinfectant and soap for washing. In Fafi, only 50% of facilities had clean water disinfectant and soap. Again, this was comparable to Ruaraka sub-County where 60% of facilities had clean water and only 40% had disinfectant and soap.

There were job aids (AMTSL & PPH) in all (100%) facilities observed in Balambala, Fafi and Lagdera. However, only 50% of facilities in Embakasi North sub-county and 60% in Ruaraka had job aids. Finally, in Balambala, all (100%) of the facility’s health workers were easily identifiable and always in uniform/name tags. While only 50% were easily identifiable in Lagdera and Embnkasi North sub-County, only 20% were identifiable in Ruaraka sub-County. No facility staff in Fafi had uniform/name tags. See Table 7 for more details.

Human resource availability

In the health sector, human resources are an essential component of the health system, especially in the provision of basic health services and are identified as one of the six core building blocks of a health system. Health workforce (HCWs) is one of the investment areas as envisioned in the Kenya Health Policy 2014-2030. SDG3 particularly target 3b seeks to increase health financing and support the health workforce in developing countries this calls to substantially increase the recruitment, capacity building, training, and retention of the health workforce. Across the levels of care, most providers indicated to have had training in the last month as shown in Figure 1 below.

Figure 1. Health worker training in the MCH

Respectful care

The FGDs revealed that some of the providers were harsh. One respondent went through labour for a long and was mishandled during delivery which led to her child developing Cerebral palsy.

“Some either public or private health centers are not good: health workers are rude, do not respond to patient’s needs, some need to be bribed to help deliver” -Respondent one-(Embakasi North Sub-County, Nairobi County).

The women also proposed the introduction adolescent / teenage-friendly MCH services for young mothers.

“The young mothers should not be put together with other old mothers. This will address the stigma of the experience which is a great barrier to accessing MCH services among adolescents” -Respondent one - (Embakasi North Sub-County, Nairobi County).

Distance to the health facilities

The distance from the respondents’ homes to the facilities ranged between 800m to 44kms. Findings from FGDs indicated that most women would walk to the facility or ride a donkey those from Garissa, others hired taxis, used of public transport while others reported they used motorbikes to seek services from the facility these were the affordable means to the nearest facility. Some respondents experienced challenges with distance and high transport costs, harsh weather conditions and high levels of insecurity. Lack of transportation was worse at night, when there was trepidation by motorbike riders.

“Security is a challenge, especially at night and people give birth on the way especially when the hospital is far. The motorcycle rider who mostly are men tend to refuse to carry expectant mothers due to the fear that they might give birth on the way” -Respondent one-. (Korogocho, Ruaraka sub-county, Nairobi county)

Social Norm

The majority of the women, visiting levels 2, level 3, and level 4 facilities, disagreed that the local culture is a barrier to accessing services at the health facility those who utilized level 2 facilities agreed that the services offered at the health facility are locally acceptable based on the context.

Figure 2. Culture and accessing services

On the contrary, social norms influenced male involvement in MCH activities. The men indicated during their FGDs that socio-cultural barriers and feminization of MCH activities mainly influenced male participation in MCH services.

“Some cultures make it hard for us to participate in seeking MCH services.” –Respondent three – (Fafi sub-County, Garissa County).

Moreover, men’s economic roles conflict with MCH activities. Some respondents mentioned their prolonged absence from home as a barrier to active participation in MCH matters.

“Most MCH services are attended by women because it is difficult to sit among women in the waiting area in the name of escorting the spouse” -Respondent four-(Embakasi North Sub-County, Nairobi County).

Affordability of MCH services from the users view

Some of the respondents indicated that the MCH services were either affordable or offered free of charge. A few felt that MCH services were not affordable especially for diagnostic services such as an ultrasound conducted during ANC visits.

“Yes, is affordable in these public health facilities except when one is referred to other hospitals there is an additional cost of transport or for the medicines that are not available.” -Respondent one-(Korogocho, Ruaraka sub-county, Nairobi County)

“The services are not affordable and especially in case an ultrasound is required.” -Respondent two-. (Korogocho, Ruaraka sub-county, Nairobi County)

Affordability also influenced the patients’ preferences and choice of health facility. Most of the respondents indicated that they prefer public hospitals because most services are available and free of charge or at low/affordable costs. They are good services offered by qualified medics.

“Many men prefer public health facilities since they are very cheap and affordable and right to the standard.” Respondent one– (Ruaraka Sub-County, Nairobi County).

4. Discussion

Quality of health care is the level to which wellbeing administrations for people/populaces improve the probability of wanted wellbeing out- comes (Nady et al., 2018; Hassan & Farag. 2019; Hassan 2020). The results of this study demonstrate major deficiencies in the quality of MCH services in both counties. While the assessed facilities had the seven signal functions of BEmONC, there is a conspicuous lack of infrastructural prerequisites to function at the very basic level in providing essential routine MCH services and emergency care. This finding is consistent with that of several studies that have cited poor infrastructure as a driver to the poor MCH outcomes (Adam et al., 2005; Gerein et al., 2006; Ukachukwu et al., 2009; World Health Organization, 2005). Inadequate MCH infrastructure constrains the capacity to provide quality MCH services in Nairobi and Garissa counties.

The lack of available theaters for conducting caesarian sections and the lack of resuscitation equipment for newborns, which bestows the ability to handle obstetric complications is the prime concern. Orji et al. concluded that the major factor causing delay to treatment is theatre-related (Orji et al., 2006). Another issue is the lack of an ambulance for emergency referrals. The Kenya Health Sector Referral Implementation guideline 2014-2018 provides a rationalized framework for a functional county referral mechanism for patients, specimens, and consultants. Unfortunately, the referral system in the country is a major national problem that needs to be addressed urgently. Delays in receiving appropriate facility-based care (delay three), for women facing pregnancy related complications contribute significantly to maternal mortality. A recent enquiry into maternal deaths in Kenya reported that 46.8 of women who died were referred, and 53.2 of these referrals died at the point of the first admission. Securing referral linkages and health facility readiness for rapid and correct patient management are needed to reduce the impact of these delays within the health system (Chavane et al., 2018). In addition, there is a challenge with the transfusion facilities for both counties as they lack proper storage for blood and cannot perform blood transfusions. This has a particular impact on women with pregnancy and delivery-related complications and with severe life-threatening anaemia.

Equally noteworthy, is the dearth of legitimate safe abortion services in both counties. Unsafe abortion is responsible for the deaths of nearly 2,600 women and girls in Kenya every year, which translates to seven deaths every day (Report: Lives at Stake as More Kenyan Women and Girls Opt for Unsafe Abortion despite Constitutional Protections |Center for Reproductive Rights, n.d.). This finding points to the great inequality in the risk of dying because of an abortion. Women are at an increased risk of acute and chronic abortion complications such as infertility and chronic pelvic pain which can be prevented if every woman has access to legitimate safe abortion when required. The Kenyan High Court ruled that safe abortion care is a fundamental right in a landmark verdict that protects patients and healthcare providers from arbitrary arrests and prosecution (IPPF, 2022). In both counties, oxytocin had a higher availability than misoprostol and calcium gluconate. The availability of misoprostol for safe abortion, PAC, and PPH could avert more maternal deaths than other large-scale interventions in developing countries (Prata et al., 2009).

The study findings also reveal that practices do not always reflect adequate implementation of clean delivery practices. Both counties lack clean bedsheets, towels, and sterile code ties. These findings mirror results published by (Moyer et al., 2012) who reported that many recommended clean delivery practices were ignored in Ghana. The results provide an important backdrop against which future interventions can be planned to improve the way infants are handled upon delivery to reduce infections. In addition, there is evidence of disrespect and abuse especially among young mothers. The finding was in line with that of (Bohren et al., 2015) who reported that many women experience disrespect and abuse during childbirth. Disrespect and abuse must, however, be addressed by centering women’s perceptions and needs, both from a human rights perspective and because negative childbirth experiences reduce utilization of health services.

Social norms also exacerbate systematic and long-standing inequities in the MCH service utilization, especially in Garissa County. While male involvement in MCH programs has been associated with positive reproductive health outcomes globally (Bawah, 2002) (Terefe & Larson, 1993), few men participate in MCH services. FGDs with the men revealed that they have adequate knowledge of the type of support they ought to give to their partners during pregnancy though they still find their participation to be unnecessary. Thoughtful restructuring of MCH programs to increasingly engage men could strengthen male involvement. Also, an understanding of the dynamics of male influence is therefore crucial in negotiating compromises to improve their involvement in MCH programs (Aborigo et al., 2018).

Access to MCH services is also constrained by security concerns especially at night. This may cause travel fares to be significantly higher at night making it harder for women who already found day fare rates as prohibitive to access facilities. Pregnant women are then faced with conundrums on “when”, “where” and “how” to reach hospitals when in an emergency. While the decision-making is a shared activity, the available options vary depending on their socioeconomic status (Banke-Thomas, n.d.). The net result of this is prolonged delays, with many women left alone to find their way or seek the services of a traditional birth attendant which may reverse gains made in improving maternal and neonatal survival. This calls for efforts to be put in place to improve the travel experiences of women through significant road-infrastructural improvements, establishing partnerships with specific taxi companies and behavior change of drivers.

A key limitation in this study was selection bias and generalizability. We used a purposive sample from facilities in Nairobi and Garissa Counties. The findings may, therefore, not be representative in the other areas of the country. Nonetheless, this is one of the most comprehensive studies on MCH service delivery involving both clinical and non-clinical providers in different levels of health facilities.

5. Conclusions

All the facilities visited in Nairobi and Garissa counties have quite a good coverage on MCH services and the population can access to maternal, newborn, and child health services easily. This is an indication that efforts towards scaling up the uptake of MCH services in Kenya are reaping good results. However, the delivery of quality maternal healthcare services was found to likely be impeded by inadequate availability of maternal medicine, compromised space or room for ANC and Neonatal service delivery, inadequate availability of infrastructure and equipment, lack of enough essential medical supplies and cost of associated with maternal and child health services. In the facilities visited in Nairobi and Garissa Counties, there were no sufficiently equipped theaters to handle operations, nor do they have the capacity to conduct any blood transfusion services when they need to. There is a dire need to fulfil the infrastructural, social and logistical challenges in health facilities for increased access, utilization and better MCH outcomes.

Conflicts of Interest

The authors declare that they have no conflicts of interest.